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Activity Number:
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76
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Type:
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Contributed
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Date/Time:
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Sunday, August 6, 2006 : 8:00 PM to 9:50 PM
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Sponsor:
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Biopharmaceutical Section
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| Abstract - #307112 |
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Title:
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Data Simulation Methodologies for Determining Sample Size Requirements To Test Gene-Drug Interactions in Genetically Pre-Screened Populations
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Author(s):
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Kimberly Lowe*+ and James Ranger-Moore and Patricia Thompson
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Companies:
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University of Arizona College of Public Health and University of Arizona College of Public Health and Arizona Cancer Center
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Address:
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1940 S. Hermosa Drive, Tucson, AZ, 85713,
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Keywords:
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pharmacogenetics ; gene-drug interactions ; data simulation ; sample size
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Abstract:
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Testing gene-drug interactions in randomized controlled trials is often unfeasible due to large sample size requirements and loss of power. We illustrate data simulation methodologies that account for variant allele frequencies under a range of effect sizes to identify sample sizes sufficiently powered to test specific gene-drug interactions. It is hypothesized that sample size requirements can be minimized if subjects are pre-screened for polymorphisms of interest and the resulting genetic information used as inclusion criteria to enrich study populations. A candidate gene-drug interaction between flavin monooxygenase 3 (FMO-3)and sulindac (trade name Clinoril) was used to model this hypothesis. There was greater than a 10% reduction in the required sample size to test the gene-drug interaction among simulated genetically-enriched study populations, assuming 80% power.
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